%0 Conference Paper %1 Szumlanski:2011:ESN:2018936.2018958 %A Szumlanski, Sean %A Gomez, Fernando %B Proceedings of the Fifteenth Conference on Computational Natural Language Learning %C Stroudsburg, PA, USA %D 2011 %I Association for Computational Linguistics %K thomas toread wikisempaths %P 190--199 %T Evaluating a semantic network automatically constructed from lexical co-occurrence on a word sense disambiguation task %U http://dl.acm.org/citation.cfm?id=2018936.2018958 %X We describe the extension and objective evaluation of a network¹ of semantically related noun senses (or <i>concepts</i>) that has been automatically acquired by analyzing lexical cooccurrence in Wikipedia. The acquisition process makes no use of the metadata or links that have been manually built into the encyclopedia, and nouns in the network are automatically disambiguated to their corresponding noun senses without supervision. For this task, we use the noun sense inventory of WordNet 3.0. Thus, this work can be conceived of as augmenting the WordNet noun ontology with unweighted, undirected <i>related-to</i> edges between synsets. Our network contains 208,832 such edges.</p> <p>We evaluate our network's performance on a word sense disambiguation (WSD) task and show: a) the network is competitive with WordNet when used as a stand-alone knowledge source for two WSD algorithms; b) combining our network with WordNet achieves disambiguation results that exceed the performance of either resource individually; and c) our network outperforms a similar resource that has been automatically derived from semantic annotations in the Wikipedia corpus. %@ 978-1-932432-92-3

@inproceedings{Szumlanski:2011:ESN:2018936.2018958, abstract = {We describe the extension and objective evaluation of a network¹ of semantically related noun senses (or <i>concepts</i>) that has been automatically acquired by analyzing lexical cooccurrence in Wikipedia. The acquisition process makes no use of the metadata or links that have been manually built into the encyclopedia, and nouns in the network are automatically disambiguated to their corresponding noun senses without supervision. For this task, we use the noun sense inventory of WordNet 3.0. Thus, this work can be conceived of as augmenting the WordNet noun ontology with unweighted, undirected <i>related-to</i> edges between synsets. Our network contains 208,832 such edges.</p> <p>We evaluate our network's performance on a word sense disambiguation (WSD) task and show: a) the network is competitive with WordNet when used as a stand-alone knowledge source for two WSD algorithms; b) combining our network with WordNet achieves disambiguation results that exceed the performance of either resource individually; and c) our network outperforms a similar resource that has been automatically derived from semantic annotations in the Wikipedia corpus.}, acmid = {2018958}, added-at = {2012-09-21T15:35:07.000+0200}, address = {Stroudsburg, PA, USA}, author = {Szumlanski, Sean and Gomez, Fernando}, biburl = {https://www.bibsonomy.org/bibtex/240e9ad0189e1dcb4d4423c8b16d50aa4/psinger}, booktitle = {Proceedings of the Fifteenth Conference on Computational Natural Language Learning}, description = {Evaluating a semantic network automatically constructed from lexical co-occurrence on a word sense disambiguation task}, interhash = {74c6ffe0515b0996ae7ec30be2625a75}, intrahash = {40e9ad0189e1dcb4d4423c8b16d50aa4}, isbn = {978-1-932432-92-3}, keywords = {thomas toread wikisempaths}, location = {Portland, Oregon}, numpages = {10}, pages = {190--199}, publisher = {Association for Computational Linguistics}, series = {CoNLL '11}, timestamp = {2012-09-25T15:29:29.000+0200}, title = {Evaluating a semantic network automatically constructed from lexical co-occurrence on a word sense disambiguation task}, url = {http://dl.acm.org/citation.cfm?id=2018936.2018958}, year = 2011 }